Best Practices for Debugging Errors in Logistic Regression with Python

Optimizing performance using unstructured, real-world data

Much has been written about the basics of Logistic Regression (LR) — its versatility, time-tested performance, even the underlying math. But knowing how to implement LR successfully and debug inevitable errors is much more challenging to do. That information lives deep in QA websites, academic papers, or simply comes with experience.

The reality is, not every output will be as clean as the iconic iris dataset, swiftly classifying flower …

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